(self)
| 3003 | self.assertTrue(math.isnan(X.pdf(float('NaN')))) |
| 3004 | |
| 3005 | def test_cdf(self): |
| 3006 | NormalDist = self.module.NormalDist |
| 3007 | X = NormalDist(100, 15) |
| 3008 | cdfs = [X.cdf(x) for x in range(1, 200)] |
| 3009 | self.assertEqual(set(map(type, cdfs)), {float}) |
| 3010 | # Verify montonic |
| 3011 | self.assertEqual(cdfs, sorted(cdfs)) |
| 3012 | # Verify center (should be exact) |
| 3013 | self.assertEqual(X.cdf(100), 0.50) |
| 3014 | # Check against a table of known values |
| 3015 | # https://en.wikipedia.org/wiki/Standard_normal_table#Cumulative |
| 3016 | Z = NormalDist() |
| 3017 | for z, cum_prob in [ |
| 3018 | (0.00, 0.50000), (0.01, 0.50399), (0.02, 0.50798), |
| 3019 | (0.14, 0.55567), (0.29, 0.61409), (0.33, 0.62930), |
| 3020 | (0.54, 0.70540), (0.60, 0.72575), (1.17, 0.87900), |
| 3021 | (1.60, 0.94520), (2.05, 0.97982), (2.89, 0.99807), |
| 3022 | (3.52, 0.99978), (3.98, 0.99997), (4.07, 0.99998), |
| 3023 | ]: |
| 3024 | self.assertAlmostEqual(Z.cdf(z), cum_prob, places=5) |
| 3025 | self.assertAlmostEqual(Z.cdf(-z), 1.0 - cum_prob, places=5) |
| 3026 | # Error case: variance is zero |
| 3027 | Y = NormalDist(100, 0) |
| 3028 | with self.assertRaises(self.module.StatisticsError): |
| 3029 | Y.cdf(90) |
| 3030 | # Special values |
| 3031 | self.assertEqual(X.cdf(float('-Inf')), 0.0) |
| 3032 | self.assertEqual(X.cdf(float('Inf')), 1.0) |
| 3033 | self.assertTrue(math.isnan(X.cdf(float('NaN')))) |
| 3034 | |
| 3035 | @support.skip_if_pgo_task |
| 3036 | @support.requires_resource('cpu') |
nothing calls this directly
no test coverage detected